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Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification

The evolution of the manufacturing sector coupled with advancements in digital twin technology has precipitated the extensive integration of digital twin robotic arms within the industrial domain. Notwithstanding this trend, there exists a paucity of studies examining the interaction of these roboti...

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Detalles Bibliográficos
Autores principales: Wu, Wenyu, Li, Mingrui, Hu, Jincheng, Zhu, Shuwei, Xue, Chengqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490699/
https://www.ncbi.nlm.nih.gov/pubmed/37688057
http://dx.doi.org/10.3390/s23177602
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author Wu, Wenyu
Li, Mingrui
Hu, Jincheng
Zhu, Shuwei
Xue, Chengqi
author_facet Wu, Wenyu
Li, Mingrui
Hu, Jincheng
Zhu, Shuwei
Xue, Chengqi
author_sort Wu, Wenyu
collection PubMed
description The evolution of the manufacturing sector coupled with advancements in digital twin technology has precipitated the extensive integration of digital twin robotic arms within the industrial domain. Notwithstanding this trend, there exists a paucity of studies examining the interaction of these robotic arms in virtual reality (VR) contexts from the user’s standpoint. This paper delves into the virtual interaction of digital twin robotic arms by concentrating on effective guidance methodologies for the input of their target motion trajectories. Such a focus is pivotal to optimize input precision and efficiency, thus contributing to research on the virtual interaction interfaces of these robotic arms. During empirical evaluations, metrics related to human–machine interaction, such as objective operational efficiency, precision, and subjective workload, were meticulously quantified. Moreover, the influence of disparate guidance methods on the interaction experience of digital twin robotic arms and their corresponding scenarios was investigated. Consequent findings offer pivotal insights regarding the efficacy of these guidance methods across various scenarios, thereby serving as an invaluable guide for future endeavors aiming to bolster interactive experiences in devices akin to digital twin robotic arms.
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spelling pubmed-104906992023-09-09 Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification Wu, Wenyu Li, Mingrui Hu, Jincheng Zhu, Shuwei Xue, Chengqi Sensors (Basel) Article The evolution of the manufacturing sector coupled with advancements in digital twin technology has precipitated the extensive integration of digital twin robotic arms within the industrial domain. Notwithstanding this trend, there exists a paucity of studies examining the interaction of these robotic arms in virtual reality (VR) contexts from the user’s standpoint. This paper delves into the virtual interaction of digital twin robotic arms by concentrating on effective guidance methodologies for the input of their target motion trajectories. Such a focus is pivotal to optimize input precision and efficiency, thus contributing to research on the virtual interaction interfaces of these robotic arms. During empirical evaluations, metrics related to human–machine interaction, such as objective operational efficiency, precision, and subjective workload, were meticulously quantified. Moreover, the influence of disparate guidance methods on the interaction experience of digital twin robotic arms and their corresponding scenarios was investigated. Consequent findings offer pivotal insights regarding the efficacy of these guidance methods across various scenarios, thereby serving as an invaluable guide for future endeavors aiming to bolster interactive experiences in devices akin to digital twin robotic arms. MDPI 2023-09-01 /pmc/articles/PMC10490699/ /pubmed/37688057 http://dx.doi.org/10.3390/s23177602 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Wenyu
Li, Mingrui
Hu, Jincheng
Zhu, Shuwei
Xue, Chengqi
Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title_full Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title_fullStr Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title_full_unstemmed Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title_short Research on Guidance Methods of Digital Twin Robotic Arms Based on User Interaction Experience Quantification
title_sort research on guidance methods of digital twin robotic arms based on user interaction experience quantification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490699/
https://www.ncbi.nlm.nih.gov/pubmed/37688057
http://dx.doi.org/10.3390/s23177602
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